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mk:llms

Generate llms.txt files from project documentation following the llmstxt.org spec. Use when asked to create AI-friendly documentation indexes, generate llms.txt, or make a project discoverable by AI assistants.

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See how to install

Files included (3)

  • SKILL.md4.3 KB
  • references/llms-txt-spec.md1.5 KB
  • scripts/generate-llms-txt.py10.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

llms.txt Generator

Generate llms.txt files — LLM-friendly markdown indexes of project documentation.

Path convention: Commands below assume cwd is $CLAUDE_PROJECT_DIR (project root). Prefix paths with "$CLAUDE_PROJECT_DIR/" when invoking from subdirectories.

When to Use

  • Project needs LLM-friendly documentation index
  • User asks for "llms.txt", "LLM documentation", "AI-friendly docs"
  • Publishing docs site and want AI discoverability
  • After major documentation updates (Phase 6 Reflect)

Explicit: /mk:llms [path] [--full]

Workflow Integration

Operates in Phase 6 (Reflect) or on-demand. Output supports the documenter agent.

Arguments

FlagEffect
(no args)Scan ./docs directory
pathScan specific directory
--fullAlso generate llms-full.txt with inline content
--output pathCustom output location (default: project root)
--url baseBase URL prefix for links

Scripts

Script-first approach — the Python script handles all deterministic work (scanning, extracting, categorizing, generating). Claude only reviews and improves the output.

# Generate llms.txt (script does the heavy lifting)
.claude/skills/.venv/bin/python3 .claude/skills/llms/scripts/generate-llms-txt.py \
  --source ./docs [--output .] [--base-url https://example.com/docs] [--full]

# Preview metadata first (Claude reviews before generating)
.claude/skills/.venv/bin/python3 .claude/skills/llms/scripts/generate-llms-txt.py \
  --source ./docs --json

Process

  1. Run script — execute generate-llms-txt.py --source <path> --json to preview metadata
  2. Review metadata — check project name, description, file categorization
  3. Generate — run script again without --json to produce llms.txt
  4. Review output — read generated llms.txt, improve descriptions if needed
  5. Validate — check: H1 present, blockquote summary, valid link format, Optional section last
  6. If --full: review llms-full.txt for completeness

Output Format

# {Project Name}

> {Brief project description with essential context.}

## {Section Name}

- [{Doc Title}]({url}): {Brief description}
- [{Another Doc}]({url}): {What this covers}

## Optional

- [{Less Important Doc}]({url}): {Supplementary info}

References

ReferenceWhen to loadContent
llms-txt-spec.mdStep 4 — generatingFull llmstxt.org specification rules

Failure Handling

FailureRecovery
No .md files foundReport "No documentation found in {path}"
No H1 in doc fileUse filename as title, warn user
Output path not writableSuggest alternative path

Constraints

  • Never fabricate documentation content — only index what exists
  • Follow llmstxt.org spec strictly
  • Keep descriptions concise — one sentence per entry

Gotchas

  • Python venv required: run .claude/scripts/bin/setup-workflow once from the project root before invoking this skill. Re-run after upgrading the toolkit.

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